LocalAI/docs/content/model-compatibility/diffusers.md

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disableToc = false
title = "🧨 Diffusers"
weight = 4
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[Diffusers](https://huggingface.co/docs/diffusers/index) is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. LocalAI has a diffusers backend which allows image generation using the `diffusers` library.
![anime_girl](https://github.com/go-skynet/LocalAI/assets/2420543/8aaca62a-e864-4011-98ae-dcc708103928)
(Generated with [AnimagineXL](https://huggingface.co/Linaqruf/animagine-xl))
Note: currently only the image generation is supported. It is experimental, so you might encounter some issues on models which weren't tested yet.
## Setup
This is an extra backend - in the container is already available and there is nothing to do for the setup.
## Model setup
The models will be downloaded the first time you use the backend from `huggingface` automatically.
Create a model configuration file in the `models` directory, for instance to use `Linaqruf/animagine-xl` with CPU:
```yaml
name: animagine-xl
parameters:
model: Linaqruf/animagine-xl
backend: diffusers
# Force CPU usage - set to true for GPU
f16: false
diffusers:
pipeline_type: StableDiffusionXLPipeline
cuda: false # Enable for GPU usage (CUDA)
scheduler_type: euler_a
```
## Local models
You can also use local models, or modify some parameters like `clip_skip`, `scheduler_type`, for instance:
```yaml
name: stablediffusion
parameters:
model: toonyou_beta6.safetensors
backend: diffusers
step: 30
f16: true
diffusers:
pipeline_type: StableDiffusionPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps,clip_skip"
scheduler_type: "k_dpmpp_sde"
cfg_scale: 8
clip_skip: 11
```
## Configuration parameters
The following parameters are available in the configuration file:
| Parameter | Description | Default |
| --- | --- | --- |
| `f16` | Force the usage of `float16` instead of `float32` | `false` |
| `step` | Number of steps to run the model for | `30` |
| `cuda` | Enable CUDA acceleration | `false` |
| `enable_parameters` | Parameters to enable for the model | `negative_prompt,num_inference_steps,clip_skip` |
| `scheduler_type` | Scheduler type | `k_dpp_sde` |
| `cfg_scale` | Configuration scale | `8` |
| `clip_skip` | Clip skip | None |
| `pipeline_type` | Pipeline type | `StableDiffusionPipeline` |
There are available several types of schedulers:
| Scheduler | Description |
| --- | --- |
| `ddim` | DDIM |
| `pndm` | PNDM |
| `heun` | Heun |
| `unipc` | UniPC |
| `euler` | Euler |
| `euler_a` | Euler a |
| `lms` | LMS |
| `k_lms` | LMS Karras |
| `dpm_2` | DPM2 |
| `k_dpm_2` | DPM2 Karras |
| `dpm_2_a` | DPM2 a |
| `k_dpm_2_a` | DPM2 a Karras |
| `dpmpp_2m` | DPM++ 2M |
| `k_dpmpp_2m` | DPM++ 2M Karras |
| `dpmpp_sde` | DPM++ SDE |
| `k_dpmpp_sde` | DPM++ SDE Karras |
| `dpmpp_2m_sde` | DPM++ 2M SDE |
| `k_dpmpp_2m_sde` | DPM++ 2M SDE Karras |
Pipelines types available:
| Pipeline type | Description |
| --- | --- |
| `StableDiffusionPipeline` | Stable diffusion pipeline |
| `StableDiffusionImg2ImgPipeline` | Stable diffusion image to image pipeline |
| `StableDiffusionDepth2ImgPipeline` | Stable diffusion depth to image pipeline |
| `DiffusionPipeline` | Diffusion pipeline |
| `StableDiffusionXLPipeline` | Stable diffusion XL pipeline |
## Usage
### Text to Image
Use the `image` generation endpoint with the `model` name from the configuration file:
```bash
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "<positive prompt>|<negative prompt>",
"model": "animagine-xl",
"step": 51,
"size": "1024x1024"
}'
```
## Image to Image
https://huggingface.co/docs/diffusers/using-diffusers/img2img
An example model (GPU):
```yaml
name: stablediffusion-edit
parameters:
model: nitrosocke/Ghibli-Diffusion
backend: diffusers
step: 25
f16: true
diffusers:
pipeline_type: StableDiffusionImg2ImgPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps,image"
```
```bash
IMAGE_PATH=/path/to/your/image
(echo -n '{"image": "'; base64 $IMAGE_PATH; echo '", "prompt": "a sky background","size": "512x512","model":"stablediffusion-edit"}') |
curl -H "Content-Type: application/json" -d @- http://localhost:8080/v1/images/generations
```
## Depth to Image
https://huggingface.co/docs/diffusers/using-diffusers/depth2img
```yaml
name: stablediffusion-depth
parameters:
model: stabilityai/stable-diffusion-2-depth
backend: diffusers
step: 50
# Force CPU usage
f16: true
diffusers:
pipeline_type: StableDiffusionDepth2ImgPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps,image"
cfg_scale: 6
```
```bash
(echo -n '{"image": "'; base64 ~/path/to/image.jpeg; echo '", "prompt": "a sky background","size": "512x512","model":"stablediffusion-depth"}') |
curl -H "Content-Type: application/json" -d @- http://localhost:8080/v1/images/generations
```